• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>3rd International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS 2003 Jun 16-18, 2003 Prague, Czech Republic >Forgiveness in Strategies in Noisy Multi-agent Environments
【24h】

Forgiveness in Strategies in Noisy Multi-agent Environments

机译：嘈杂的多智能体环境中策略的宽恕

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Game theory has been widely used in modelling interactions among autonomous agents. One of the most oft-studies games is the iterated prisoner's dilemma. Prevalent assumptions in the majority of this work have been that no noise is present and that interactions and gestures by agents are interpreted correctly. In this paper, we discuss two classes of strategies that attempt to promote cooperation in noisy environments. The classes of strategies discussed include: forgiving strategies which attempt to re-establish mutual cooperation following a period of mutual defection; and memory-based strategies which respond to defections based on a longer memory of past behaviours. We study these classes of strategies by using techniques from evolutionary computation which provide a powerful means to search the large range of strategies' features.
机译：博弈论已被广泛用于对自治主体之间的交互进行建模。反复研究囚徒困境是最常研究的游戏之一。在这项工作的大部分中，普遍的假设是不存在噪音，并且正确解释了代理的交互和手势。在本文中，我们讨论了两类试图在嘈杂环境中促进合作的策略。讨论的策略类别包括：宽容策略，在相互背叛一段时间后试图重新建立相互合作；以及基于记忆的策略，可根据对过去行为的较长记忆来应对缺陷。我们使用进化计算技术研究这些策略类别，这些技术提供了一种强大的手段来搜索各种策略的特征。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号